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We propose and verify a method for color-based cluster segmentation of the various tissues from ectocervix. That method uses a simplified compartment-like analysis, aiming for a Gaussian Mixture Model (GMM)-tailored segmentation. The tissues of interest are the cervical canal (CC), the columnar epithelium (CE), the squamous epithelium (SE) and the transformation zone (TZ) the latter known as area...
Dimension reduction methods have been commonly used for content-based multimedia indexing and retrieval. In this paper, we investigate the use of a mapping by adaptive threshold (MAT) method for dimension reduction of feature data. The proposed MAT method is implemented and compared to two other well-known dimension reduction methods, namely Principal Component Analysis and Multidimensional Scaling...
The problem of linear prediction for multiple channels of data sampled at different rates is considered. The prediction error filters in this case are periodically time-varying. A Levinson-type recursion is developed for the linear prediction parameters. A sliding window formulation is also developed.
Maximum Likelihood (ML) and Multi-Stage Weighted Linear / Non-Linear Least Squares (MS-WLLS / MS-WNLS) estimation methods are formulated for non-stationary Functional Series Time-dependent ARMA (FS-TARMA) models. The methods' effectiveness, as well as their superiority over Ordinary Linear / Non-Linear Least Squares (OLLS / ONLS) type methods not accounting for innovations serial heteroscedasticity,...
Canonical Correlation Analysis (CCA) is a classical tool in statistical analysis that measures the linear relationship between two or several data sets. In [1] it was shown that CCA of M = 2 data sets can be reformulated as a pair of coupled least squares (LS) problems. Here, we generalize this idea to M > 2 data sets. First, we present a batch algorithm to extract all the canonical vectors through...
Motion compensation is an essential problem in video coding. The main drawback of the usual motion estimation methods is that they divide the images into blocks or patches which do not correspond to moving objects. In this paper, we propose a method to estimate the motion in regions instead of blocks. We define a cost functional to estimate simultaneously the segmentation and the motion of the regions...
The Direction of Arrival estimation algorithm ESPRIT is capable of estimating the angles of arrival of N narrowband source signals using M > N anechoic sensor mixtures from a uniform linear array (ULA). Using a similar parameter estimation step, the DUET Blind Source Separation algorithm can demix N > 2 speech signals using M = 2 anechoic mixtures of the signals. We introduce here the DUET-ESPRIT...
Using the framework of Reproducing Kernel Hilbert Spaces, we develop a new sequence kernel that measures similarity between sequences of observations. We then apply it to a text-independent speaker verification task using the NIST 2004 Speaker Recognition Evaluation database. The results show that incorporating our new sequence kernel in an SVM training architecture not only yields performance significantly...
In this paper, we investigate chaotic-type features for universal speech steganalysis. These features are used in the design of linear regression classifier. The steganalyzer is tested on watermarking and steganographic methods. Experimental results show the potential of chaotic-type features for their discriminatory power to be used in steganalysis. We believe that the integration of chaotic-type...
The application of adaptive systems trained in a supervised manner to approximate the Neyman-Pearson detector is considered. The general expression of the function approximated when using the LMSE criterion is calculated. To evaluate the sensitivity of the decision rule based on this function to threshold variations, a novel strategy is proposed based on the calculus of the partial derivative of the...
In this paper, we consider frame expansions derived from biorthogonal wavelet bases for building multiple descriptions with low redundancy constraints. Such constraints rise the problem of perfect reconstruction of the associated decompositions in the absence of quantization or channel errors, which requires special attention and therefore will be detailed in this work. We will show that several schemes...
Lossless video compression is a novel research area, but it is gaining widespread importance. As an example, in digital cinema the post-production chain requires all the information captured by digital cameras, and any data loss is not tolerated. On the other hand, the camera sensors size is expected to grow up to 4k × 2k pixels at 10 bit per pixel per component, and cameras output frame-rate up to...
This paper presents a novel approach for tracking feature points in video sequences. In this method, the image intensity is represented by a 3D deformable surface model. Tracking is performed by exploiting a by-product of explicit surface deformation governing equations. The proposed method was compared with the well known KLT tracking algorithm, in terms of tracking accuracy and robustness. The obtained...
We formulate the phase vocoder - an audio synthesis method very closely related to inverse short time Fourier Transform synthesis - as a Gaussian state space model and demonstrate simulation results on interpolation of missing values. The audio signal is modelled as a superposition of quasi-sinusoidal signals generated by a linear dynamical system. The advantage of our “generative” perspective is...
Clinicians' decision for mechanical aid discontinuation is a challenging task that involves a complete knowledge of a great number of clinical parameters, as well as its evolution in time. Respiratory pattern variability appears as a useful extubation readiness indicator, and thus can be used as an informative feature in a statistical pattern recognition framework. Reliable assessment of this variability...
In this paper we address the problem of Bayesian blind source separation with generalized p-Gaussian priors for the sources (also known as Lp priors). These kind of priors are useful when modeling sparse sources (spiky signals, wavelet coefficients …) The corresponding posterior laws are non linear and either maximum a posteriori (MAP) or posterior mean estimates are computationally difficult to obtain...
This paper deals with the signal processing techniques to be applied in the reception of the Search And Rescue (SAR) system COSPAS/SARSAT distress beacons. The receiver unit has to estimate time delays and Doppler shifts of a set of satellite-relayed replicas of the original beacon in order to compute the position where the device has been activated. The Cramér-Rao Bound (CRB), which determines the...
In this paper we propose an information theory based generic method for complex Independent Component Analysis (ICA). Expressions for the complex score function are derived. The method exploits the full second order structure of complex signals. It combines a preprocessing step called the strong-uncorrelating transform (SUT) [10] with ICA methods that use the proposed complex score function. The method...
A generalized blind equalization scheme, insensitive to phase shifts introduced by the channel and small carrier phase offsets, is derived. Multiple constraints optimization techniques have been used in the development of the proposed algorithm. This scheme is an improved version of a dual mode modified constant modulus algorithm (MCMA). It uses the principle of minimal disturbance to induce robustness...
In this paper we derive a new design of the Convex Variable Step-Size (CVSS) algorithm, based on measurements obtained with LMS algorithm. Computer simulations are provided to support the proposed approach.
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